Which company lookalike API is the most accurate?

On long-list relevance (Precision@100) measured on identical seed companies, Parallel is the current leader, while PredictLeads leads on top-of-list precision (Precision@10). Precision@10, @50, and @100 are reported per vendor and refresh per snapshot.

Is there a single best lookalike / similar-companies API?

Not on every axis. Top-of-list quality (are the first ~10 right?), long-list quality (are the first ~100 right?), and coverage can favor different providers. The benchmark reports each one per vendor on identical inputs, so the numbers are directly comparable.

What's the most accurate lookalike API for a closed-won play?

The benchmark ranks the four providers on avg Precision@100 against identical B2B seed companies, scored by an LLM judge on identical inputs — the current leader is on the ranking above.

How is lookalike API accuracy measured?

Every provider gets the same seed companies and the same input; an LLM judge scores how many of the companies each returns are actually relevant, reported as Precision@10 / 50 / 100. Every cell is reproducible from the raw API request/response and the exact judge prompt, published openly.

benchmarks/lookalikes/most accurate lookalike API

lookalike benchmark · ranking

The most accurate company lookalike API

Short answer, from an independent test on identical seed companies: Parallel leads on long-list relevance (Precision@100). PredictLeads leads on top-of-list precision (Precision@10). "Most accurate" isn't one number — it depends on whether you act on the first ~10 results or the first ~100 — so this benchmark reports both, on the same inputs, fully reproducible.

route by workflow

There is no single “best” company lookalike API — this independent benchmark points to a different winner depending on how you will use the results. Pick the workflow that matches yours:

Low volume, high accuracyPredictLeadstop 10 P@10 95.8%
Reps hand-work a handful of accounts, so the top of the list has to be right. Sharpest top-of-list precision in the benchmark.
High volume, broad reachParallellong list P@100 67.5%
A big list runs through automated sequences, so relevance has to hold deep into the results. Best long-list precision in the benchmark.
Market / TAM sizingParallelrelevant 3,242
You are counting the universe of similar companies, not actioning a shortlist. Returns the most relevant companies across the cohort.
Real-time in-product featurePredictLeadsavg latency 739 ms
A live “similar companies” lookup called on page-load, where response time is the constraint. Fastest average latency in the benchmark.

Full ranking, per-seed evidence, and average latency: the lookalike benchmark →

[01] the ranking

Company lookalike APIs, ranked by relevance

Every provider gets the same seed companies and the same input; an LLM judge scores how many of the companies each returns are actually relevant. Precision@100 is the headline accuracy number — of the 100 companies you paid for, how many are usable. Ranked highest-first:

#	Provider	Precision@100 (long-list)	Precision@10 (top-of-list)
1	Parallel	67.5%	74.8%
2	Extruct	61.2%	74.8%
3	Ocean.io	56.5%	73.2%
4	Exa	52.4%	95.0%
5	Discolike	35.2%	43.0%
—	PredictLeads	—	95.8%
—	CUFinder	—	37.5%

Numbers are point-in-time against a specific dataset and refresh as seeds are added — they don't generalize indefinitely. Every cell is reproducible from the raw request/response and judge prompt. See the full per-seed matrix and methodology →

[02] which axis

Top-of-list vs long-list precision

A provider can lead the top-10 and fall off over the full 100, or hold relevance deep without topping the first handful. Current leader on each cutoff:

If you care about…	The axis	Current leader
Acting on a short, hand-checked list	Top-of-list precision (Precision@10)	PredictLeads
Building a large target list / TAM	Long-list relevance (Precision@100)	Parallel